( en | de | ru )

 

Disambiguation of "Anastasio, Mark A."

Author of the publication

copydeleteadd this publication to your clipboard
Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks.

, and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160D. SPIE, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Mark A Nusselein

Mark A Awabdy

Stefano Anastasio

Mark A Nusselein

Mark Yampolsky

Maßnahmen zur Sicherung von E2E-QoS bei verketteten Diensten. Uni München, (2009)
 

Other publications of authors with the same name

Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression., , , , and . Medical Imaging: Digital Pathology, volume 10956 of SPIE Proceedings, page 1095604. SPIE, (2019)Learning efficient channels with a dual loss autoencoder., , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160C. SPIE, (2020)Autoencoder embedding of task-specific information., , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 1095207. SPIE, (2019)Application of DatasetGAN in medical imaging: preliminary studies., , , and . Medical Imaging: Image Processing, volume 12032 of SPIE Proceedings, SPIE, (2022)Investigation of adversarial robust training for establishing interpretable CNN-based numerical observers., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12035 of SPIE Proceedings, SPIE, (2022)Assessing regularization in tomographic imaging via hallucinations in the null space., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11599 of SPIE Proceedings, SPIE, (2021)Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements., , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160Q. SPIE, (2020)Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks., and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11316 of SPIE Proceedings, page 113160D. SPIE, (2020)A survey of computational frameworks for solving the acoustic inverse problem in three-dimensional photoacoustic computed tomography., , and . CoRR, (2019)Learning stochastic object model from noisy imaging measurements using AmbientGANs., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 109520M. SPIE, (2019)